similar to: Uneven y-axis scale

Hi all! I've got a datstructure like this: subject week value 1 1 4 2 1 8 3 1 3 4 1 5 1 2 5 2 2 6 3 2 2 4 2 6 1 3 3 2 3 7 3 3 3 4 3 7 I'd like to plot the mean of 'value' against week. Is there a direct way of doing this or do I have to make a new structure with the calculated values and then plot it? All the best! -- ########################################### Kare

I'm writing an publication in two column format and need to shrink some plots. After increasing the axis labels it does not look nice at all. The y-axis label and tick labels almost touch each other and the x-axis tick labels expand into the plot instead of away from it. Is there a better way than "cex" to control the: 1) font size of axis and tick labels 2) font thickness 3)

Hi all. If I run the simple regression when x is a categorical variable ( x <- factor(x) ): > MyFit <-coxph( Surv(start, stop, event) ~ x ) How can I get the overall p-value on x other than for each dummy variable? > anova(MyFit) does NOT provide that information as previously suggested on the list. All the best, Kare [[alternative HTML version deleted]]

I'd like to avoid looping through an array in order to change values in the array as it takes too long. I red from an earlier post it can be done by "do.call" but never got it to work. The Idea is to change the value of "y" according to values in "x". Wherever "x" holds the value 3, the corresponding value in "y" should be set to 1. So I

R-gurus... I've got a 5 column dataframe where I'd like to plot each ID's "b" against "c" with "b" in ascending order (within the same ID). How do I sort "b" so that the other variables are altered equally? ID a b c d 101 1 240 26.7 21.85 101 2 335 21.8 21.85 101 3 1387 26.6 21.85 101 4 877 24.1 21.85

Hi r-helpers... Why do I get this strange huge jump of 36524 days when changing "origin" from 1969-01-01 to 1968-12-31. It should still be close to zero! This really messes up my calculations of follow-up times in my analyses. > julian(strptime("010169", format = "%d%m%y"),origin = as.Date("1969-01-01")) > Time difference of -0.04166667 days >

Is there a function providing more descriptive statistics than "summary()"? I'm working with a coxph analyses and would like to have more info on certain numbers. If my call is something like: Call: coxph(formula = Surv(followup, CasesCancer) ~ age + BMI + parity + HRT) I'd like to know: * How many CasesCancer was excluded (not only the total number of excluded due to

Dear R-helpers, I'm for sure not familiar with R, but it seem like a nice sofware tool, so I've decided to try using it. Here is my problem I just can't figure out: I'd like to do least square fit of a straight horizontal (a = 0) line y = ax + b through some data points x = (3,4,5,6,7,8) y = (0.62, 0.99, 0.83, 0.69, 0.76, 0.82) How would i find b????? All the best, Ked

Hello r-help! I have data with two kind of ratings on status of 100 occupations. The first kind of rating is on the percieved "objective" status that these occupations have in society at large, and the second kind or rating is on the status that the respondents think that these occuption *should* have. The ratings were originally integer values in the rage 1-9, but in the current data,

May be you are also not familiar with statistic. the solution of min \sum_{i=1}^{n} (y_{i}-b)^{2} is the mean. So the solution is b<-mean(y) Justin BEM Elève Ingénieur Statisticien Economiste BP 294 Yaoundé. Tél (00237)9597295. ----- Message d'origine ---- De : Kåre Edvardsen <ked@nilu.no> À : R-help <r-help@stat.math.ethz.ch> Envoyé le : Vendredi, 8 Décembre 2006,

Hello, I have a question about the y-axis of plots. Actually I had about 60 values. About 80 percent of these values are less than 0.2, then the other 20 percent values are more than 4,max is 10. So when I plot these values together, the y-axis's range will go 0 to 10, and my major values (80% values <0.2) will be pressed around 0 on the bottom, while other several dots will scatter in

Hi! First of all: I'm a newbie to both statistics and R, so please be patient with me... I do however, like R because I've been programming (pascal, IDL, perl, C etc) and designing models since -92, but never related to statistics. Ok, here we go: I've got a set of 15 people, all of them observed over 10 weeks (10 analysed blood samples) with - let us kall it the A-value - influenced

Hi Mitch, Thank you for the response. 1. You don't need to build the library with `-fsanitize-coverage=...`, using `-fsanitize=fuzzer-no-link,address` should be sufficient. - Acknowledged 2. (although you can actually build object files/shared libraries with -fsanitize=fuzzer, and the libFuzzer main won't be linked, if this makes your build process easier). - with just the *fuzzer

I have a new device that takes measurements anywhere from every second, to every 15 minutes (depending on changes). The matrix has a date, time and Y column (Y is the measurement). For three days it is 25,000 rows. How do I average the measurements by every 30 minutes so my matrix is 48 rows per day? I have been working on this and cannot figure out a simple method. Any ideas? Thank you. ----- In

Hi I have a vector m: m [1] "ABC transporters" [2] "2" [3] "Acetyl-CoA" [4] "1" [5] "Energie" [6] "1" [7] "FAD Biosynthese"

Hi R-helpers I would like to produce a histogram with uneven bins (e.g., 0, 1-2, 3-5, 6-10, 10-20, >20) but I would like the resulting bars to be the same width ( i.e., a bar's width would not be proportional to its corresponding bin size). Also, the x and y axes of my histograms frequently (almost always, actually) extend beyond the axis labels (i.e., there are unlabeled bars). I would

I have 4 univariate time series that I believe have correlation between them, I want to create a VAR model between them all. However I have an issue as 3 of them are the same length, however the 4th is smaller. meaning that i cannot use the 4th variable , is there anyway R can get round this issue? > length(tstemp) [1] 746 > length(tspres) [1] 746 > length(tswind) [1] 746 >

I admit I belong to a small group of not-too-bright people who still aspire to use LLVM. But I kind of see that as a highly valuable feature, insofar I convert this fact into something constructive (such as FAQ writing) :-) I actually did recommend people to disable their antivirus solution for two reasons - the aforementioned "virus" and the speed slowdown that they'll experience,

I am trying to import a file of daily index closing prices in business time which excludes weekends and holidays so deltat is not constant. My file looks like the following: date close 2003.0055 47.05 2003.0082 45.71 2003.0164 43.45 2003.0192 42.96 2003.0219 44.56 2003.0247 42.99 2003.0274 42.28 2003.0356 41.74 etc. >From what I saw in the EuStockMarkets file, it appears

i have > x [1] 1 2 3 4 5 6 > y [1] 34 5 6 > z<-cbind(x,y) > z x y [1,] 1 34 [2,] 2 5 [3,] 3 6 [4,] 4 34 [5,] 5 5 [6,] 6 6 i don't want recycling, instead can we put NA /0 like below> z x y [1,] 1 34 [2,] 2 5 [3,] 3 6 [4,] 4 NA [5,] 5 NA [6,] 6 NA & want distance matrix -- View this message in context: